Applied AI founders should win when models get better, not fear them
srimisra · x · 2026-07-22
A founder note argues that applied AI companies should be the point where model progress diffuses into market segments. Because applications differ wildly in product, go-to-market, and price-performance needs, labs are more likely to integrate down into inference than move up into applications.
The practical test is simple: if a model gets twice as good, should your customer get twice the value and your capture scale proportionally? If you feel worse when models improve, your company may be sitting in the wrong part of the stack.
Related event: AI Consensus: Models Are No Longer the Moat, Application Layer Is(2 posts)→
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